Parameter Set for Computer-Assisted Texture Analysis of Fetal Brain
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Gentillon et al. BMC Res Notes (2016) 9:496 DOI 10.1186/s13104-016-2300-3 BMC Research Notes RESEARCH ARTICLE Open Access Parameter set for computer‑assisted texture analysis of fetal brain Hugues Gentillon1,2*, Ludomir Stefańczyk1, Michał Strzelecki2 and Maria Respondek‑Liberska3 Abstract Background: Magnetic resonance data were collected from a diverse population of gravid women to objectively compare the quality of 1.5-tesla (1.5 T) versus 3-T magnetic resonance imaging of the developing human brain. MaZda and B11 computational-visual cognition tools were used to process 2D images. We proposed a wavelet-based parameter and two novel histogram-based parameters for Fisher texture analysis in three-dimensional space. Results: Wavenhl, focus index, and dispersion index revealed better quality for 3 T. Though both 1.5 and 3 T images were 16-bit DICOM encoded, nearly 16 and 12 usable bits were measured in 3 and 1.5 T images, respectively. The four- bit padding observed in 1.5 T K-space encoding mimics noise by adding illusionistic details, which are not really part of the image. In contrast, zero-bit padding in 3 T provides space for storing more details and increases the likelihood of noise but as well as edges, which in turn are very crucial for differentiation of closely related anatomical structures. Conclusions: Both encoding modes are possible with both units, but higher 3 T resolution is the main difference. It contributes to higher perceived and available dynamic range. Apart from surprisingly larger Fisher coefficient, no significant difference was observed when testing was conducted with down-converted 8-bit BMP images. Keywords: Histogram, Wavelets, Computer-assisted radiology, Hugues Gentillon, Teleradiology, Prenatal development, Fetal brain, Mazda, b11, Medical cybernetics, Artificial intelligence, Computational visual cognition Background MRI replacing USG during pregnancy examination Computer is a non-biological copy of the human brain. In terms of safety, ultrasonography (USG) remains the As its use increases day-by-day in medicine, various gold standard for prenatal central nervous system (CNS) transdisciplinary approaches emerge. Among them is imaging [1]. It is used for prevention and diagnosis of texture analysis, the evolving cybernetics of radiology. congenital malformation [2, 3]. Nevertheless, there are This experiment is a translational study seeking to objec- cases which benefit from alternative imaging techniques tively compare the quality of 1.5-tesla (1.5 T) versus 3-T like 1.5 or 3 T MRI [4–9]. Besides spotting maternal magnetic resonance imaging (MRI) of the developing abnormalities, supplemental information from magnetic human brain (Fig. 1), in order to determine whether the resonance imaging is also crucial for identification of extra administrative cost is worthy for the patient and fetal anatomy and pathology [10, 11]. MRI is also being the healthcare system. First there was a need to develop increasingly used as correlative imaging modality in an objective methodology to collect and process the data pregnancy—because it uses no ionizing radiation, has and subsequently justify its necessity and dispel distrust no known teratogenic effects, provides excellent soft-tis- of financial burden. sue contrast, and has multiple planes for reconstruction and large field of view, allowing better depiction of neu- roanatomy in fetuses with large or complex anomalies [12–15]. Compared to magnetic resonance imaging, USG is more affordable and widely used in many countries, *Correspondence: [email protected] 1 Department of Radiology and Diagnostic Imaging, Barlicki University as a radiologic tool in routine examination of pregnant Hospital, Medical University of Lodz, Lodz, Poland women, especially in the detection of fetal anomalies, at Full list of author information is available at the end of the article about 20th week of gestation [2, 3]. On the other hand, © The Author(s) 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Gentillon et al. BMC Res Notes (2016) 9:496 Page 2 of 18 Fig. 2 Ultrasonography (USG) vs. magnetic resonance imaging (MRI). Fig. 1 “Do you see what I see?”. Fetal brain. a Left 1.5 T. b Right 3 T. This Fetal MRI was used as a complimentary modality to USG. a USG. b figure was incorporated and so‑titled in this manuscript to illustrate MRI that magnetic resonance (MR) images can be used for evaluation of achromatic vision and sensitivity to change in grayscale quality between different subjects. For fair comparison, this exercise should be blinded. It is recommended to have at least two radiologists, for integration into medical practice. To this date, texture if not available, medically‑trained practitioners or any volunteers analysis is used in pre-diagnosis of the globally pandemic (blinded) and one examiner (also blinded) to look at the images side‑by‑side, on two medical‑diagnostic monitors, engineered for disease of tuberculosis [27–29]. In Bangladesh, for exam- 16‑bit display (same brand/model in natively flat display mode: i.e. ple, radiologists and radio-technicians quickly screen without any added enhancements). All in‑computer/in‑monitor RT patients displaying tuberculosis (TB) signs with CAD4TB (real‑time) editing features must be turned off (incl. hardware/soft‑ texture analysis software [30–33]. This medical applica- ware rendering): n.b. 16‑bit of true data has more room for “contrast tion of texture analysis is sponsored by The World Health booster”—which is essentially an illusion, as a result of post‑editing artifacts, not really part of the image. In this investigation, volunteers Organization, at a mere cost of $3 per CAD4TB test. were asked to identify the images unlabeled (, of course). It was Only patients pre-diagnosed TB-positive by CAD4TB observed that both images were equally sharp (in pass‑through software receive the more expensive molecular examina- mode), for a normal, naked human eye. There flows the explanation tion known as GeneXpert TB Diagnosis and Resistance for the research goal to mathematically determine which MR modal‑ Test [30–33]. In the aforementioned example, an increase ity actually produces images with more captured details. Both images were 16‑bit encoded, and the difference could not be measured via in the rate of early- detection of TB has been reported in “perceived dynamic range” (visible details). With computer vision clinics where texture analysis is used as a pre-diagnostic software, 1.5/3 T images can be numerically decoded to accurately tool [30–33]. Apart from image encoding statistics, other assess “available dynamic range” (visible/invisible details) factors also affect how clinicians perceive medical image appearance: e.g. acutance or subjective quality factor, human eye’s contrast sensitivity function, modulation 1.5 and 3 T MRI scanners produce superior CNS images transfer function or spatial frequency response, image (Fig. 2) but are not cost-effectively built. These units are displayed height, viewing distance, positioning of the massive and expensive [16–20]. They are mostly availa- subjects (stand, seat), radiology LCD (liquid crystal dis- ble in big-budget hospitals and wealthy medical research play) screen characteristics (anti-glare, glossy, size, reso- centers. Because of such disadvantages, carrying research lution, calibration), etc [34–36]. with MRI is more likely to be impeded. As a result, lit- tle information is known about its relevance to potential Wavelets‑based texture analysis beneficiaries. MRI is bureaucratically recommended only Wavelets are texture analysis parameters which classify if it is essential in some health care systems administrated intrinsic properties of an image into matrix layers, and by a central office (e.g. Sweden) [21]. Physicians are even therefore they are very powerful tools for differentiating liable for part of MRI examination cost in some territo- and matching patterns in regions of interest. Wavelets are ries (e.g. Poland) [22, 23]. Thus relevance to beneficiaries used, for example, in forensic investigation to match fin- is likely to be affected in such health care systems. gerprints [37], in diagnostic radiology to detect suspected diseases [38], and in many other applications where digi- What is texture analysis? tal imaging is needed [37]. Texture analysis is an artificial process involving quanti- fication of image quality by means of parametric features Histogram‑based texture analysis to characterize regions of interest (ROI) [24–26]. While To fully grasp the concept behind the methodology used texture analysis is still far from replacing the clinician in this experiment, it is important to first comprehend or eye, some of its features warrant further consideration at least have a minimum knowledge about the purpose, Gentillon et al. BMC Res Notes (2016) 9:496 Page 3 of 18 functionality, and usefulness of histogram in digital imag- bits = 28 = 256). In other words, a 16-bit image would be ing. Just as the aforementioned brain images in Fig. 1, the down-sample in order to display its geometric represen- quality and texture of every shape in Fig. 3 may not be tation on such computational histograms (Figs. 4, 5, 6). A interpreted in the same way by different pairs of human Histogram display in MaZda, on the other hand, does not eyes. graphically display pixel values larger than 255. However, Histogram parameters are digital imaging tools which it is able to quantify 16-bit DICOM (Digital Imaging and analyze textural characteristics of a picture by measuring Communications in Medicine), evaluate quality of differ- their quality [39, 40].